The goal of a machine learning regression problem is to predict a single numeric value. ... See the image in Figure 2. The demo decision tree has 7 nodes. Because of the binary structure, the number ...

For decision tree classification, the variable to predict is most often ordinal-encoded (0, 1, 2 and so on) The numeric predictors do not need to be normalized to all the same range -- typically 0.0 ...

Leaving out neural networks and deep learning, which require a much higher level of computing resources, the most common algorithms are Naive Bayes, Decision Tree, Logistic Regression, K-Nearest ...

Decision-tree-based machine-learning methods allow, in theory, for determining the learning path. However, severe constraints exist that make any explanation extremely difficult. Let’s look at ...